Neural Network in Computational Neuroscience
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Computational Neuroscience and Neuroinformatics".
Deadline for manuscript submissions: 31 July 2024 | Viewed by 398
Special Issue Editor
Interests: medical image analysis; magnetic resonance imaging; pattern recognition; neuroscience; machine learning; deep learning; computer-aided diagnosis and detection
Special Issue Information
Dear Colleagues,
Neural Networks in Computational Neuroscience is a rapidly advancing field that intersects the study of biological neural networks and the artificial neural networks employed in machine learning and artificial intelligence. This interdisciplinary approach aims to understand how the brain computes and processes information, using insights from both neuroscience and computer science. Understanding the similarities and differences between biological neural networks (like those in the brain) and artificial neural networks is of great significance in the understanding, detection, and early diagnosis of various brain diseases. Developing computational models to simulate neural processes is vital, as it helps to understand how neurons and neural circuits process information. This Special Issue aims to publish novel methodologies and applications related to the above concepts. The scope of this Special Issue includes, but is not limited to, the following topics:
- Developing bio-inspired neural network models that more closely mimic the structure and function of biological neural networks, potentially leading to more efficient and robust AI systems.
- Understanding brain–computer interfaces and how neural networks can be utilized to improve BCIs, which could have profound implications for medicine, prosthetics, and human–computer interaction.
- Neural coding and information processing: exploring how the brain encodes information, with potential applications in improving the processing of AI systems process and their interpretation of data.
- Using neural networks to simulate brain disorders, leading to an enhanced understanding of these conditions and potential treatments.
- Novel methods to better understand neurodegenerative disease, tumors, ischemic stroke, etc.
- Using multimodal imaging and electrophysiology data for effective disease diagnosis and detection.
- Other related topics.
Dr. Ahmed Elazab
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- neural networks
- computational neuroscience
- artificial intelligence
- machine learning
- brain-computer interface
- information processing
- neural coding
- brain disorders
- novel methods
- brain imaging and electrophysiology
